Multimodal human-humanoid interaction using motions, brain nirs and spike trains

Authors:
Yasuo Matsuyama;Nimiko Ochiai;Takashi Hatakeyama;Keita Noguchi
Affiliations:
Waseda University, Tokyo, Japan;Waseda University, Tokyo, Japan;Waseda University, Tokyo, Japan;Waseda University, Tokyo, Japan
Venue:
Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction
Year:
2010

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Abstract

Heterogeneous bio-signals including human motions, brain NIRS and neural spike trains are utilized for operating biped humanoids. The Bayesian network comprising Hidden Markov Models and Support Vector Machines is designed for the signal integration. By this method, the system complexity is reduced so that that total operation is within the scope of PCs. The designed system is capable of transducing original sensory meaning to another. This leads to prosthesis, rehabilitation and gaming. In addition to the supervised mode, the humanoid can act autonomously for its own designed tasks.